This application discloses an invention which is related, generally and in various embodiments, to a system and method for identifying a targeted consumer based on both behavior and attitudes.
In the quest for new business opportunities, there has been a growing proliferation of products and services seeking to more relevantly satisfy consumer needs. This has heightened competition and furthered a desire by marketers to look for tools that can more precisely identify optimal groups of consumers. Typical targeting methods have used historical information to determine what type of consumer had previously used product/service categories or brands. These factors were used to predict which consumers would likely buy in the future.
The majority of the previous approaches to target marketing prioritized consumers based on category and volume of brand usage. Such consumer targeting efforts are largely based on demographic and geodemographic factors. One approach has been to administer a survey to measure consumer usage levels pertaining to specific products, services and brands. The surveys have also been utilized to gather general demographic information for each respondent. Standard analysis techniques have been applied to study the results and identify optimal demographic segments for targeting marketing efforts. Geodemographic systems have been utilized to categorize the entire marketplace of consumers into a specific number of neighborhood types. These neighborhood types are typically classified according to demographic factors.
Unfortunately, targeting methods based on demographics or geodemographics have several drawbacks. For example, both methods assume that all consumers within a defined demographic or geodemographic sub-set are equally attractive. As such, these methods typically do not distinguish between individual consumers within the same group. In addition, neither method considers attitudinal variables, even though attitudinal variables greatly influence the future purchasing behavior of consumers. Because of these drawbacks, volume-only marketing techniques often do not meet the financial needs or specific marketing objectives of marketers.
To enhance the results generally achieved from the traditional targeting methodologies, some methodologies have also utilized attitudinal filtering. Attitudinal filtering is utilized to identify and reach groups of consumers who tend to “think alike” with respect to their brand and market segment. Examples of such groups, which are divided based on attitudinal variables, include early adopters of high tech consumer products, risk-averse buyers of investment securities, prestige-seeking buyers of luxury automobiles, fashion conscious clothes buyers, etc. Various examples of attitudinal filtering are described in U.S. Pat. No. 7,742,072, assigned to the assignee of the instant patent application.
The grouping of potential customers using attitudinal characteristics and definitions results in segments defined by more than mere demographics and/or behaviors. For example, rather than creating a group of potential luxury car buyers based solely on demographic information like income and past purchases, attitudinally-based segments look to the reasons for purchasing behavior. In this example, instead of merely identifying a group of potential luxury car buyers, the use of attitudinal filtering allows for the grouping of potential luxury car buyers based on the reason for wanting to purchase a luxury car (e.g., seeking prestige, professional appearance, etc.).
In brief, known targeting methodologies which utilize behavioral segmentation to identify a targeted consumer do not take into account the valuable information provided by the consumer's attitudes, and known methodologies which utilize attitudinal segmentation to identify a targeted consumer do not take into account the valuable information provided by the consumer's behavior. Thus, known targeting methodologies would be significantly improved by utilizing both behavioral and attitudinal segmentation criteria to identify one or more targeted consumers.